摘要
针对六自由度运动模拟器经典洗出算法对环境适应性差、滤波器参数的选取受到现场调试人员经验的干扰以及空间利用率低的问题,对洗出算法增加了反馈调节设计,同时提出了一种基于混沌理论自适应萤火虫算法(FA)的参数优化方法。利用人体感知变化规则将模糊控制环节增加到洗出算法结构中;对萤火虫初始位置通过混沌序列进行初始化,利用自适应变化的方式改变吸引度系数,同时引入多样性变异策略,以增强全局最优解的搜索能力。对比MATLAB/Simulink仿真实验的洗出数据发现:改进后的洗出算法提高了空间利用率,增加了参数选取灵活度,优化了参数固定对环境适应性差的问题,平台运行稳定性和逼真程度均得到了提升。
Regarding the problems that the classical washout algorithm of the 6-DOF motion simulator has poor adaptability to the environment,the selection of filter parameters is affected by the experience of on-site debugging personnel,and the space utilization rate is low,added feedback adjustment design to the washing algorithm,meanwhile a parameter optimization method based on chaos theory adaptive firefly algorithm(FA)is proposed.Add fuzzy control to the washing algorithm structure by utilizing human perception change rules;The initial position of fireflies is initialized through chaotic sequences,and the attraction coefficient is adaptively changed.At the same time,diverse mutation operations are introduced to enhance the search ability for the global optimal solution.Comparing the washout data from MATLAB/Simulink simulation experiments,The improved washout algorithm has increased space utilization,increased flexibility in parameter selection,optimized the problem of poor environmental adaptability caused by fixed parameters,and improved the stability and realism of the platform operation.
作者
王福凯
刘曰涛
于智勇
邹大林
温尚林
祝保财
WANG Fukai;LIU Yuetao;YU Zhiyong;ZOU Dalin;WEN Shanglin;ZHU Baocai(School of Mechanical Engineering,Shandong University of Technology,Zibo 255049,China)
出处
《组合机床与自动化加工技术》
北大核心
2025年第7期1-5,9,共6页
Modular Machine Tool & Automatic Manufacturing Technique
基金
国家自然科学基金资助项目(51805299)
山东省自然科学基金项目(ZR2022ME185)。
关键词
运动模拟器
经典洗出算法
萤火虫算法
混沌理论
motion simulator
classic washout algorithm
firefly algorithm
chaos theory
